# interpreting meta regression results in R

I performed meta-regression in R and got the following results:

Mixed-Effects Model (k = 21; tau^2 estimator: ML)

tau^2 (estimated amount of residual heterogeneity):     0.1994 (SE = 0.0706)
tau (square root of estimated tau^2 value):             0.4466
I^2 (residual heterogeneity / unaccounted variability): 92.23%
H^2 (unaccounted variability / sampling variability):   12.88
R^2 (amount of heterogeneity accounted for):            7.18%

Test for Residual Heterogeneity:
QE(df = 19) = 465.3482, p-val < .0001

Test of Moderators (coefficient 2):
F(df1 = 1, df2 = 19) = 1.5851, p-val = 0.2233


Model Results:

              estimate      se     tval    pval    ci.lb   ci.ub
intrcpt         0.9233  0.1866   4.9495  <.0001   0.5329  1.3138  ***
participants   -0.1566  0.1244  -1.2590  0.2233  -0.4168  0.1037


Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1


My questions is that for the participants group I have divided them into 1 (younger participants) and 2 (older participants), why can't I see the breakdown of the different participants here?

• What does "estimate of participants = -0.1566" mean? – user158565 Jul 5 at 15:47
• @user158565 perhaps you should have preceded your comment with Hint, hint, ... – mdewey Jul 5 at 16:27